GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing
Year: 2022
Type: article
Abstract: Genome-wide association studies (GWAS) have made impactful discoveries for complex diseases, often by amassing very large sample sizes. Yet, GWAS of many diseases remain underpowered, especially for non-European ancestries. One cost-effective approach to increase sample size is to combine existing cohorts, which may have limited sample size or be case-only, with public controls, but this approach is limited by the need for a large overlap in variants across genotyping arrays and the scarcity of non-European controls. We developed and validated a protocol, Genotyping Array-WGS Merge (GAWMerge), for combining genotypes from arrays and whole-genome sequencing, ensuring complete variant overlap, and allowing for diverse samples like Trans-Omics for Precision Medicine to be used. Our protocol involves phasing, imputation, and filtering. We illustrated its ability to control technology driven artifacts and type-I error, as well as recover known disease-associated signals across technologies, independent datasets, and ancestries in smoking-related cohorts. GAWMerge enables genetic studies to leverage existing cohorts to validly increase sample size and enhance discovery for understudied traits and ancestries.
Source: Communications Biology
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,490
Funders: U.S. Department of Health and Human Services, Pfizer, AstraZeneca, GlaxoSmithKline, Johns Hopkins University, COPD Foundation, Sunovion, National Institutes of Health, Genentech, National Heart, Lung, and Blood Institute, National Institute on Drug Abuse, National Human Genome Research Institute, National Cancer Institute, National Institute of Environmental Health Sciences
Awards: The Integration of Trans-omics for Precision Medicine (TOPMED) and Other Heart, Lung, Blood and Sleep (HLBS) Data Sets with the Data Commons, G1052645489, G1129490614, G1270179341, G1356451498, G1689438493, G2006782615, G207790757, G2087483592, G2096685756, G2103038081, G2146332128, Rare variants and NHLBI traits in deeply phenotyped cohorts, G232264632, G2417563097, G2644038179, G2647562155, G266518826, Study of Addiction: Genetics and Environment, G2816736420, G3078883119, G3153258624, G3194560040, G3245180032, G3256118428, G3549415863, G3668601034, G377726100, G3799582765, G3811607389, G4086371180, G4279961139, Genome Wide Association Coordinating Center, G50080621, G5163278296, G5258357286, G5496802768, The Integration of Trans-omics for Precision Medicine (TOPMED) and Other Heart, Lung, Blood and Sleep (HLBS) Data Sets with the Data Commons, NHLBI Data Stage Coordinating Center, G6134854566, G631129105, G635002275, G6615318374, Harnessing Knowledge of Gene Function in Brain Tissue for Discovering Biology Underlying Heroin Addiction, G7093047072, G7383526863, G747687783, G7522350138, The Integration of Trans-omics for Precision Medicine (TOPMED) and Other Heart, Lung, Blood and Sleep (HLBS) Data Sets with the Data Commons, G7949433598, G80516811, G8222448866, G8267674335, Studies of Rare Genetic Variation in the Isolated Population of Sardinia, G8354759825, G8790190034, Enhancing Discovery of HIV Host Genetics using Drug Abuse and other Interactions, G9000010287, G9000054071, G9000071188, G9000091268, G9000112574, G9000122777, G9000141541, G9000146249, G9000147737, G9000176579, G9000180696, G9000228787, G954689843
OpenAlex ID: W4291004903